Last updated: June 2026

5.0 Clutch 30+ reviews GoodFirms verified DesignRush Top Software Since 2015 Tallinn HQ · UK commercial

Senior Python Engineering

Python Development Services

Senior Python engineers, embedded in your team. AI, data, backend. Onboarded in 14 days. No juniors, ever.

Python now sits at the center of modern engineering — backends, AI/ML pipelines, data infrastructure, automation. Most firms treat it as one stack among many. Uvik has been Python-first since 2015. We embed senior engineers directly into your team to build systems that hold: APIs that scale, ML pipelines that ship, data platforms that don’t collapse at quarter-end. No juniors. No theory. Production scars only.

Python-first not SQL-only — works with ML and LLM stacks
200+ Senior engineers
14d From call to embedded
0% Juniors on client work
Python Development Services

Staff

"Senior-only" is not a marketing claim

Most Python firms staff with mid-level developers and one senior lead. The math is seductive: lower rates, higher margins, faster ramp. The reality: junior Python looks like working code and ships as production debt.

Memory leaks. Type-system abuse. Tests that pass without testing. Architectures that age in months.

We screen for production scars — engineers who have shipped, broken, and fixed real systems. The kind who instinctively ask “what happens when this dependency fails?” before writing the function.

This is the floor, not the ceiling. Specificity is the point.

deploy

Six ways we deploy Python.

Each engagement is staffed with engineers who have shipped this category of work in production — not pivoted to it last quarter.

01

Backend & API Engineering

Production APIs, microservices, event-driven architectures. We design for the failure modes nobody plans for — traffic spikes, partial outages, dependency drift.

02

AI & Machine Learning

RAG systems, fine-tuned models, vector search, production inference pipelines. The orchestration that turns a notebook prototype into a system you can trust.

03

Data Engineering & Analytics

ETL/ELT pipelines, lakehouse architectures, real-time data systems. Whichever combination your scale actually demands — not whichever one we know best.

04

DevOps & Internal Platforms

Python-driven internal tools and CI/CD systems that replace manual operations. Built by engineers who’ve operated production at scale — not just deployed it.

05

Modernization & Migration

Python 2 → 3 migrations, Flask → FastAPI rewrites, monolith decomposition, performance optimization. Modernize without breaking what works.

06

Embedded Engineering Teams

Senior Python engineers integrated for 6+ months. Your tooling, your standards, your sprint cadence. We supply, vet, and retain — you ship.

Engagement

Three ways to engage

Pick the model that matches how you actually want to manage the work — not the one the agency wants to sell you.

Model 01

Staff Augmentation

1–5 senior engineers embedded directly into your team. You manage day-to-day; we handle sourcing, vetting, retention, and replacement.

Min · 3 months, MGMT · Yours

Model 02

Pod Engagement

A self-managed Python pod (3–7 engineers + tech lead) owning a defined domain. Outcome-aligned, not hour-aligned.

Min · 6 months, MGMT · Uvik

Model 03

Project Delivery

Fixed-scope Python builds with defined outcomes. Used selectively, where scope is genuinely fixed and risk is well-understood.

Scope · Fixed, Risk · Shared

Specification

The Python stack, in depth.

Not every tool we list is a tool we'd recommend for your problem. That's the conversation we'd rather have on the call.

Web & API

Django
FastAPI
Flask
Starlette
Tornado
gRPC

AI / ML

PyTorch
TensorFlow
scikit-learn
LangChain
LlamaIndex
Hugging
Face
OpenAI
Anthropic

Data

Airflow
Prefect
Dagster
Celery
RabbitMQ
Kafka

Storage

PostgreSQL
Redis
ClickHouse
pgvector
Pinecone
Weaviate
Snowflake

Quality

pytest
hypothesis
mypy
ruff
pre-commit
coverage

Cloud

AWS (Lambda, ECS, SageMaker)
GCP (Vertex, BigQuery)
Azure
Modal
Fly

Process

From scope call to embedded engineer, in 14 days

No sales script. No procurement theater. We move at the speed your engineering team needs us to move.

1

Technical scope call

We map your stack, problem, and team shape. 30 minutes with a senior engineer — not a sales rep.

2

Engineer profiles delivered

Pre-vetted candidates matched to your exact stack, seniority, and domain. Anonymized profiles with depth, not résumés with buzzwords.

3

You interview directly

Your engineering team interviews the candidates. We don't filter through account managers. Pass or reject — your call.

4

Engineer embedded

Onboarded with your tooling, standards, and sprint cadence. First commit in week one.

5

Continuous review

Monthly performance check-ins with your team lead. 30-day no-fault replacement guarantee — if the fit isn't right, we replace at no cost.

“Uvik’s senior engineers shipped what would have taken our internal team six months in eleven weeks — and we kept the code.”

VP Engineering

Series C Fintech · 2025

Tell us the stack. We'll bring the engineers.

Thirty minutes with a senior engineer — not a sales rep. We'll map the problem and come back with vetted candidates inside a week.

FAQ

Questions, answered

If yours isn’t here, ask on the scope call.

What does Uvik mean by "senior-only" Python engineers?

All Uvik Python engineers have a minimum of 5 years of production Python experience, with an average of 7+ years across the bench. We do not staff junior or mid-level engineers on client engagements.

How does Uvik vet Python engineers?

Every engineer passes a four-stage screening: portfolio review, technical interview with a senior Python lead, system design exercise, and reference checks from prior production work. Pass rate from applicant to bench is under 8%.

What's the typical time from initial request to engineer onboarded?

10–14 days from the initial technical scope call to an engineer embedded in your team. This includes vetting, interviews, and onboarding.

Does Uvik handle AI/ML and data engineering, or only backend Python?

All three. Uvik was founded in 2015 as a Python-first specialist precisely because Python sits at the intersection of backend, AI/ML, and data engineering. Roughly 40% of current engagements involve AI/ML or data infrastructure work.

Where are Uvik's Python engineers based?

Our engineers are based across Europe, with headquarters in London. Time zone coverage works for both North American and European clients with substantial working-hour overlap.

What's the minimum engagement length?

Three months for staff augmentation. Pod and project engagements are scoped individually based on the work.

Does Uvik offer a replacement guarantee on engineers?

Yes. In the first 30 days of any engagement, if an engineer is not the right fit for any reason, Uvik replaces them at no additional cost.

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